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  • 1
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    Response Surface Modeling Tolerance and Inference Error Risk Specifications: Proposed Industry Standards (2012)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: This paper reviews the derivation of an equation for scaling response surface modeling experiments. The equation represents the smallest number of data points required to fit a linear regression polynomial so as to achieve certain specified model adequacy criteria. Specific criteria are proposed which simplify an otherwise rather complex equation, generating a practical rule of thumb for the minimum volume of data required to adequately fit a polynomial with a specified number of terms in the model. This equation and the simplified rule of thumb it produces can be applied to minimize the cost of wind tunnel testing.
    Keywords: Statistics and Probability
    Type: AIAA Paper 2012-2859 , NF1676L-15008 , 28th Aerodynamic Measurement Technology, Ground Testing, and Flight Testing Conference; Jun 25, 2012 - Jun 28, 2012; New Orleans, LA; United States
    Format: application/pdf
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  • 2
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    Bayesian Revision of Residual Detection Power (2013)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: This paper addresses some issues with quality assessment and quality assurance in response surface modeling experiments executed in wind tunnels. The role of data volume on quality assurance for response surface models is reviewed. Specific wind tunnel response surface modeling experiments are considered for which apparent discrepancies exist between fit quality expectations based on implemented quality assurance tactics, and the actual fit quality achieved in those experiments. These discrepancies are resolved by using Bayesian inference to account for certain imperfections in the assessment methodology. Estimates of the fraction of out-of-tolerance model predictions based on traditional frequentist methods are revised to account for uncertainty in the residual assessment process. The number of sites in the design space for which residuals are out of tolerance is seen to exceed the number of sites where the model actually fails to fit the data. A method is presented to estimate how much of the design space in inadequately modeled by low-order polynomial approximations to the true but unknown underlying response function.
    Keywords: Statistics and Probability
    Type: NF1676L-22320 , AIAA Ground Testing Conference; Jun 24, 2013 - Jun 26, 2013; San Diego, CA; United States
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  • 3
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    Propagation of Computational Uncertainty Using the Modern Design of Experiments (2007)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: This paper describes the use of formally designed experiments to aid in the error analysis of a computational experiment. A method is described by which the underlying code is approximated with relatively low-order polynomial graduating functions represented by truncated Taylor series approximations to the true underlying response function. A resource-minimal approach is outlined by which such graduating functions can be estimated from a minimum number of case runs of the underlying computational code. Certain practical considerations are discussed, including ways and means of coping with high-order response functions. The distributional properties of prediction residuals are presented and discussed. A practical method is presented for quantifying that component of the prediction uncertainty of a computational code that can be attributed to imperfect knowledge of independent variable levels. This method is illustrated with a recent assessment of uncertainty in computational estimates of Space Shuttle thermal and structural reentry loads attributable to ice and foam debris impact on ascent.
    Keywords: Statistics and Probability
    Type: NATO-RTO AVT-147 Symposium on Computational Uncertainty in Military Vehicle Design; Dec 03, 2007 - Dec 06, 2007; Athens; Greece
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  • 4
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    Analysis of Variance in the Modern Design of Experiments (2010)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: This paper is a tutorial introduction to the analysis of variance (ANOVA), intended as a reference for aerospace researchers who are being introduced to the analytical methods of the Modern Design of Experiments (MDOE), or who may have other opportunities to apply this method. One-way and two-way fixed-effects ANOVA, as well as random effects ANOVA, are illustrated in practical terms that will be familiar to most practicing aerospace researchers.
    Keywords: Statistics and Probability
    Type: AIAA Paper 2010-1111 , LF99-9992 , 48th AIAA Aerospace Sciences Meeting; Jan 04, 2010 - Jan 07, 2010; Orlando, FL; United States
    Format: application/pdf
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